In seismic exploration field, carbonate rocks, as an unconventional reservoir, usually develop into large Karst caves, which show beads-shaped seismic response characteristics (“beads” for short) in a seismic profile. The “beads” imaging is closely related to a migration velocity model. Specifically, when the migration velocity is too large, the “beads” imaging will bend upwards and have a relatively weak energy; when the migration velocity is too small, the “beads” imaging will bend downwards and have a relatively weak energy; and when the migration velocity has a just right value, the “beads” imaging is convergent and has a strongest energy. However, since conventional velocity spectrum picking is based on a relatively large grid, the migration velocity model is inaccurate. As a result, the “beads” imaging usually bends upwards or downwards. The inaccurate “beads” imaging will not facilitate the following drilling and further reservoir prediction. In order to solve the problem of non-convergence of the “beads” imaging of the carbonate rocks unconventional reservoir, a least-squares migration imaging method is generally used in the prior art to obtain a convergent “beads” imaging.
However, it is discovered that, the calculation consumption of the least-squares migration imaging method is relatively large. The method depends highly on an initial model and the convergence is very easy to fall into a local extremum, which will result in that the beads-shaped seismic response characteristics never converge. A full waveform inversion method is facing a same problem. Therefore, it is necessary to develop an automatic focus identification method and a system for a Karst cave reservoir which can improve a reservoir prediction accuracy.
The information disclosed in the background of the present disclosure only aims at facilitating in-depth understanding on general background technology of the present disclosure, which cannot be considered as admitting or implying in any manner the information constituting conventional knowledge well known for those skilled in the art.